Senior AI Infrastructure Engineer

Join VideoAmp as a Senior AI Infrastructure Engineer, where you will play a crucial role in designing and executing agentic workflow systems that enhance our platform APIs and AI-powered customer experiences. This high-impact individual contributor position will involve architecting and owning production-critical systems, driving evaluation-driven development, and collaborating with internal engineering teams. You will have the opportunity to shape the future of VideoAmp's agentic platform and contribute to the growth of our AI infrastructure.

• Architect and own production-critical systems serving live customers, operating in a rigorous evaluation-driven culture.
• Design and implement multi-tenant isolation, rate limiting, and caller-attribution systems as direct enterprise customers use MCP tools.
• Lead evaluation-driven development, design golden scenario suites, automated CI/CD evaluation pipelines, and regression detection across all workflows.

• Familiarity with A2A protocols and long-running, durable workflows
• Track record of working across engineering, product, and operations teams to drive alignment and rollout of shared infrastructure and capabilities
• Experience with MCP or equivalent tool-layer abstractions for exposing platform capabilities to AI agents, or for building agents that consume them
• Multi-tenant system design: experience implementing rate limiting, caller attribution, tenant isolation, and external support surfaces for shared production APIs
• Strong Go (Golang) engineering skills; backend systems are Go-first. Proficiency in Python and SQL is also expected
• 6+ years of software engineering experience, with 1+ years in AI/ML infrastructure, LLM platform engineering, or agentic system development
• Practical experience designing agent loops for production systems, including context and state management across turns, prefix caching for latency and cost, and coordinating multi-step task execution
• Production API design and operations: strong background in resource-based API design and experience building or consuming developer-facing platform APIs at scale, including on-call and incident response
• Deep experience with LLM APIs such as Anthropic or OpenAI, including prompt engineering and tool use/function calling
• Ability to produce design documents, postmortems, and system diagrams that create shared understanding across technical and non-technical stakeholders
• Experience building automated test and evaluation suites for LLM-based systems, including golden scenarios, regression detection, and quality gates in CI/CD
• AdTech or media measurement familiarity, including linear TV, OTT, CTV, and digital video
• Open-weights model experience such as Llama or Mistral
• Fine-tuning experience such as LoRA or PEFT
• Familiarity with Rust